Drone maps mines to explore unsafe caverns and seek out minerals

In the 2012 sci-fi film Prometheus, scientists release small drones into a mysterious tunnel complex to create a detailed 3D map of the caverns in minutes. Australian researchers plan to use a similar approach to explore parts of old mines that are unsafe to visit.

The drones, which are controlled by a pilot, will be able to carry out safety checks by monitoring the build-up of water and checking the extent of roof collapses, and search for valuable mineral deposits that may have been missed. They are being developed by Craig Lindley and his colleagues at the Commonwealth Scientific and Industrial Research Organisation, Australia’s government research agency.

The researchers’ model is based on a commercial quadcopter. It has powerful LED lights, cameras and sonar. Initially, they tried flying it using the drone’s on-board camera to guide them, an approach known as first-person-view (FPV) piloting. But this isn’t ideal for long journeys navigating labyrinthine mines without hitting the walls.

“FPV makes operating really difficult, since the space is confined and seeing in just one direction doesn’t give you good situational awareness in terms of distance to anything in other directions,” says Lindley.

So the team developed computer software called VoxelNet, which creates a 3D model of the surrounding area based on video imagery sent from the drone to a laptop. This gives the navigator a virtual view of the drone in its environment, so they can see where it is in relation to floors and walls while also looking for minerals and safety hazards.

It currently takes 20 minutes to map a 10-metre stretch of tunnel using the video data – but there may be a more efficient way.

Sonar-sensing

“Most recently, we have explored the use of sonar,” says Lindley. Sonar sensors, which use sound waves to detect objects, produce less data than video cameras. This means they can be used to create a 3D model more quickly, possibly even in real time.

Although the sonar model is less accurate, a yet-to-be-published paper shows that it provides effective navigation. Given that it uses less data and therefore less processing power, the mapping could potentially be done on-board the drone rather than sending the information to a computer first, says Lindley.

It may be a challenge to reliably operate such a drone though, says Joshua Marshall at Queen’s University in Kingston, Canada, who has also worked on underground mapping drones.

Mapping in these environments without a solid global navigation system like GPS – which can’t penetrate deep underground – can be tricky, he says, and can sometimes fail or result in areas being inaccurately mapped. “So the challenge is to do this robustly,” he says.

Because of these communication challenges, underground drones may ultimately need to be able to operate completely autonomously, says George Nikolakopoulos at Luleå University of Technology in Sweden.

Lindley and his team are continuing to improve the VoxelNet software and are also experimenting with lidar, which maps using lasers. In addition, they are running tests with data from X-ray fluorescence analyses, which detect different elements, to train machine learning to identify minerals in rock walls.